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Record W2032874530 · doi:10.1103/physreva.81.023411

Nonlinear time-dependent density-functional-theory study of ionization and harmonic generation in CO<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msub><mml:mrow/><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:math>by ultrashort intense laser pulses: Orientational effects

2010· article· lv· W2032874530 on OpenAlexafffund
Emmanuel Penka Fowe, André D. Bandrauk

Bibliographic record

VenuePhysical Review A · 2010
Typearticle
Languagelv
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsUniversité de Sherbrooke
FundersCompute Canada
KeywordsPhysicsIonizationAtomic physicsAtomic orbitalTime-dependent density functional theoryHigh harmonic generationDensity functional theoryMolecular orbitalLaserIonization energyPolarization (electrochemistry)Molecular physicsMoleculeElectronQuantum mechanicsIonPhysical chemistryChemistry

Abstract

fetched live from OpenAlex

Time-dependent density-functional-theory (TDDFT) methods are used to calculate the orientational dependence of ionization and molecular high-order harmonic generation (MHOHG) in the CO${}_{2}$ molecule as a function of laser intensity ${I}_{0}\ensuremath{\geqslant}{10}^{14}$ W$/$cm${}^{2}$ for few-cycle 800 nm laser pulses. A time-series analysis is used to confirm the recollision model in MHOHG for different density potentials. It is found that at intensities ${I}_{0}&gt;3.5\ifmmode\times\else\texttimes\fi{}{10}^{14}$ W$/$cm${}^{2}$, lower highest occupied molecular orbitals (HOMO's) contribute significantly to ionization and to the MHOHG process. This is due to the symmetry of these orbitals. Even though such lower orbitals have higher ionization potentials (IP), ionization and MHOHG processes occur when orbital densities are maximum with laser polarization direction.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.848
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0770.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.263
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations50
Published2010
Admission routes2
Has abstractyes

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Same venuePhysical Review ASame topicLaser-Matter Interactions and ApplicationsFrench-language works237,207